Can Kernel Methods Explain How the Data Affects Neural Collapse?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kothapalli, Vignesh, Tirer, Tom
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Information Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks
by: Kothapalli, Vignesh, et al.
Published: (2024)

Causally-Guided Diffusion for Stable Feature Selection
by: Malarkkan, Arun Vignesh, et al.
Published: (2026)

Does Privacy Always Harm Fairness? Data-Dependent Trade-offs via Chernoff Information Neural Estimation
by: Nichani, Arjun, et al.
Published: (2026)

Data Augmentation in Graph Neural Networks: The Role of Generated Synthetic Graphs
by: Bas, Sumeyye, et al.
Published: (2024)

Position: Let's Develop Data Probes to Fundamentally Understand How Data Affects LLM Performance
by: Wang, Shiqiang, et al.
Published: (2026)

CoT-ICL Lab: A Synthetic Framework for Studying Chain-of-Thought Learning from In-Context Demonstrations
by: Kothapalli, Vignesh, et al.
Published: (2025)

Neural Polar Decoders for Deletion Channels
by: Aharoni, Ziv, et al.
Published: (2025)

Subgraph Federated Learning via Spectral Methods
by: Aliakbari, Javad, et al.
Published: (2025)

Catastrophic Forgetting Mitigation Through Plateau Phase Activity Profiling
by: Mashiach, Idan, et al.
Published: (2025)

From Markov to Laplace: How Mamba In-Context Learns Markov Chains
by: Bondaschi, Marco, et al.
Published: (2025)

Learning in Convolutional Neural Networks Accelerated by Transfer Entropy
by: Moldovan, Adrian, et al.
Published: (2024)

Neural Beam Field for Spatial Beam RSRP Prediction
by: Guo, Keqiang, et al.
Published: (2025)

AlphaZip: Neural Network-Enhanced Lossless Text Compression
by: Narashiman, Swathi Shree, et al.
Published: (2024)

Lost and Found in Translation: Variational Diagnostics for Neural Codebook Channels
by: Hayashi, Yusuke
Published: (2026)

Interpretability as Compression: Reconsidering SAE Explanations of Neural Activations with MDL-SAEs
by: Ayonrinde, Kola, et al.
Published: (2024)

Neural Estimation of Pairwise Mutual Information in Masked Discrete Sequence Models
by: Sharma, Jai, et al.
Published: (2026)

How Many Features Can a Language Model Store Under the Linear Representation Hypothesis?
by: Garg, Nikhil, et al.
Published: (2026)

Enhancing Explainability of Graph Neural Networks Through Conceptual and Structural Analyses and Their Extensions
by: Bui, Tien Cuong
Published: (2025)

Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS
by: Obeed, Mohanad, et al.
Published: (2026)

A Machine Learning Approach for Simultaneous Demapping of QAM and APSK Constellations
by: Gansekoele, Arwin, et al.
Published: (2024)

Deep Randomized Distributed Function Computation (DeepRDFC): Neural Distributed Channel Simulation
by: Bergström, Didrik, et al.
Published: (2026)

An Information Criterion for Controlled Disentanglement of Multimodal Data
by: Wang, Chenyu, et al.
Published: (2024)

An Information-Theoretic Criterion for Efficient Data Synthesis
by: Li, Hanyu, et al.
Published: (2026)

Neural Channel Knowledge Map Assisted Scheduling Optimization of Active IRSs in Multi-User Systems
by: Chen, Xintong, et al.
Published: (2025)

Partial Information Decomposition for Data Interpretability and Feature Selection
by: Westphal, Charles, et al.
Published: (2024)

Semi-supervised Batch Learning From Logged Data
by: Aminian, Gholamali, et al.
Published: (2022)

Best Arm Identification with Possibly Biased Offline Data
by: Yang, Le, et al.
Published: (2025)

MARS: Margin and Semantic-Aware Data Augmentation for Reward Modeling
by: Bhattacharjee, Payel, et al.
Published: (2026)

Uncertainty Quantification and Data Efficiency in AI: An Information-Theoretic Perspective
by: Simeone, Osvaldo, et al.
Published: (2025)

Hierarchical Over-the-Air Federated Learning with Awareness of Interference and Data Heterogeneity
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2024)

IBB Traffic Graph Data: Benchmarking and Road Traffic Prediction Model
by: Olug, Eren, et al.
Published: (2024)

Energy-Efficient Edge Learning via Joint Data Deepening-and-Prefetching
by: Kook, Sujin, et al.
Published: (2024)

Laplace Sample Information: Data Informativeness Through a Bayesian Lens
by: Kaiser, Johannes, et al.
Published: (2025)

Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications
by: Letafati, Mehdi, et al.
Published: (2023)

Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data
by: Yang, Yuqin, et al.
Published: (2023)

Diffusion Model-Based Data Synthesis Aided Federated Semi-Supervised Learning
by: Wang, Zhongwei, et al.
Published: (2025)

Enhancing User Throughput in Multi-panel mmWave Radio Access Networks for Beam-based MU-MIMO Using a DRL Method
by: Hashemi, Ramin, et al.
Published: (2026)

Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
by: Heurtel-Depeiges, David, et al.
Published: (2024)

Understanding LLM Behaviors via Compression: Data Generation, Knowledge Acquisition and Scaling Laws
by: Pan, Zhixuan, et al.
Published: (2025)

Neural Networks Learn Generic Multi-Index Models Near Information-Theoretic Limit
by: Zhang, Bohan, et al.
Published: (2025)